Artificial Intelligence for Security and Privacy
A.Y. 2026/2027
Learning objectives
The aim of the course is to provide students with the theoretical and practical knowledge needed to understand, use, and evaluate the main artificial intelligence models and algorithms for security and privacy.
Expected learning outcomes
By the end of the course, students will be familiar with the main artificial intelligence models and algorithms applicable to security- and privacy-related problems, and will be able to apply them to real-world security and privacy scenarios.
Lesson period: Second four month period
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second four month period
Course syllabus
The course covers the main artificial intelligence models and algorithms, with a particular focus on cybersecurity and privacy. Topics include:
- Fundamentals of artificial intelligence and machine learning
- AI processing pipelines
- Artificial neural networks and deep learning
- Continual and online learning; federated learning
- Generative models and synthetic datasets
- Security and privacy issues in AI; AI methods for security and privacy
- Fundamentals of artificial intelligence and machine learning
- AI processing pipelines
- Artificial neural networks and deep learning
- Continual and online learning; federated learning
- Generative models and synthetic datasets
- Security and privacy issues in AI; AI methods for security and privacy
Prerequisites for admission
None
Teaching methods
Lectures.
Teaching Resources
Papers and slides available on the course web site (https://myariel.unimi.it/course/view.php?id=10547).
Assessment methods and Criteria
The assessment to evaluate the students' knowledge and understanding of the subject consists of a written exam. The exam includes theory questions and exercises and is closed-book. The mark is expressed in thirtieths and the grading will consider the correctness, completeness, and clarity of the answers to the questions and exercises. A minimum score of 18 is required to pass. An additional oral exam may be required if deemed necessary.
INFO-01/A - Informatics - University credits: 6
Lessons: 42 hours
Professor:
Piuri Vincenzo
Shifts:
Turno
Professor:
Piuri VincenzoProfessor(s)